Learning outcomes:

By the end of the programme, participants will be able to:

• Identify workflows suitable for AI augmentation.

• Map current-state workflows and diagnose inefficiencies.

• Prioritise AI use cases based on value, feasibility, and risk.

• Redesign a manual workflow into an AI-assisted process.

• Define human review points and risk controls.

• Produce a one-page AI Workflow Blueprint or prototype brief.

Learner deliverables:

• Current-state workflow map.

• AI opportunity matrix.

• Future-state AI-assisted workflow.

• PRD-lite / prototype brief.

• Group presentation of selected AI workflow.

Key topics include:

• Difference between AI productivity and AI transformation.

• Why AI adoption fails inside organisations. 

• Current-state workflow mapping.

• Pain-point identification and process bottlenecks.

• AI use-case discovery and prioritisation.

• Business value, feasibility, risk, and adoption-readiness scoring.

• Human-in-the-loop workflow design.

• PRD-lite / prototype brief creation.